ROAD QUALITY MONITORING & PREDICTION 2.0 

RoadEO is developing a global road quality monitoring and prediction platform advising public road authorities and commercial construction firms when and where the next road segment needs to be maintained. 

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For this we combine available traffic and environmental information with our own set of novel sensor and data sources such as crowdsourced smartphone measurements, in-vehicle sensors as well as satellite earth observation to create a unique big data pool which is being analysed and interpreted through our artificial intelligence solution.

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The provided information helps our customers to detect road wear and structural damages alike, cheaper than with specialised vehicles and better than visual bypass assessments, and allows for optimal decision making and maintenance scheduling. This results in maximised road safety, reduced cost of operations and minimised downtime for repair purposes.

CROWDSOURCED 
SENSORS

SATELLITE EARTH OBSERVATION

ARTIFICIAL INTELLIGENCE

Smartphones are the ultimate IoT sensor. They are connected to the internet, carry powerful sensors and are available all around the world. Our mobile app allows our customers and users to access these capabilities and utilise them for continuous, crowdsourced road quality monitoring.

Novel satellite instruments and services allow us to capture more frequent, sharper and complex images of our planet. We are using these opportunities to complement the data we gather on the ground and combine them to create a new source of rich insights.

While traditional approaches for road quality monitoring are usually lacking data, we generate terabytes of them every day. To quantify and predict road damages we are using powerful artificial intelligence algorithms to make sense of the data created and turn them into valuable insights.